The present embodiments relate to visually highlighting spatial structures in a volume data record.
Volume data records and corresponding three-dimensional representations play an important role not only in medicine but also in other fields such as, for example, quality assurance or geology. In a scalar volume data record, different gray-scale values correspond to different structures of the originally recorded object (e.g., different types of tissue in a human body).
Direct volume renderings (DVR) represent a colored image of the different structures within a volume by mapping different data values (e.g., gray-scale values) to different colors and opacities. Essentially, such mapping classifies the different objects detected within the data. Direct volume renderings allow fast and efficient examination of the objects.
The mapping of data values to colors and opacities is modeled in a transfer function and is typically represented by a set of piecewise linear functions PWL. A piecewise linear function includes control points, each of which defines a color and opacity in a defined position in the data histogram. Positions between adjacent control points are interpolated linearly. Generally, the quality and usefulness of a direct volume rendering largely depend on the transfer function and the extent to which the transfer function highlights the structures of interest and conceals regions that are not of interest.
The quality of the transfer function is therefore a key factor for direct volume rendering. Defining suitable transfer functions by modifying control points of the piecewise linear function is a time-consuming and complicated task. This is due to the mathematics of light integration, as approximated by direct volume rendering. The mathematics of light integration is decidedly non-linear and makes it difficult to predict the visual impression of a direct volume rendering.
Also, the nature of the transfer function and how the transfer function relates to the final rendering is not intuitive. The transfer function is defined in the data region of the histogram. Therefore, the form of the piecewise linear functions and the position of the control points along the data axis do not indicate where the classified structures are located in the image and how the classified structures overlap with one another. The overlapping of semi-transparent objects result in a mixing of colors in the final image, which is not apparent from the data domains of the transfer function. If software therefore forces a user to change the control points of the piecewise linear function directly, it is very difficult to predict the visual effect of the change. This procedure is time-consuming and difficult for inexperienced users.
Conventionally, the user edits the values of the transfer function directly. If the mapping of colors and opacities is represented using piecewise linear functions, the user edits the positions, colors, and opacities of the control points of the piecewise linear functions.